Handle case where user has multiple manual events on same camera (#15943)

* remove unused annotate file

* improve plus error messages

* formatting

.github/workflows/ci.yml

@@ -75,15 +75,6 @@ jobs:
             rpi.tags=${{ steps.setup.outputs.image-name }}-rpi
             *.cache-from=type=registry,ref=${{ steps.setup.outputs.cache-name }}-arm64
             *.cache-to=type=registry,ref=${{ steps.setup.outputs.cache-name }}-arm64,mode=max
-      - name: Build and push Rockchip build
-        uses: docker/bake-action@v3
-        with:
-          push: true
-          targets: rk
-          files: docker/rockchip/rk.hcl
-          set: |
-            rk.tags=${{ steps.setup.outputs.image-name }}-rk
-            *.cache-from=type=gha
   jetson_jp4_build:
     runs-on: ubuntu-latest
     name: Jetson Jetpack 4

.github/workflows/pull_request.yml

@@ -76,7 +76,7 @@ jobs:
         with:
           persist-credentials: false
       - name: Set up Python ${{ env.DEFAULT_PYTHON }}
-        uses: actions/setup-python@v5.1.0
+        uses: actions/setup-python@v5.3.0
         with:
           python-version: ${{ env.DEFAULT_PYTHON }}
       - name: Install requirements

benchmark.py

@@ -61,7 +61,7 @@ def start(id, num_detections, detection_queue, event):
     object_detector.cleanup()
     print(f"{id} - Processed for {duration:.2f} seconds.")
     print(f"{id} - FPS: {object_detector.fps.eps():.2f}")
-    print(f"{id} - Average frame processing time: {mean(frame_times)*1000:.2f}ms")
+    print(f"{id} - Average frame processing time: {mean(frame_times) * 1000:.2f}ms")
 
 
 ######

docker/hailo8l/requirements-wheels-h8l.txt

@@ -1,12 +1,12 @@
-appdirs==1.4.4
-argcomplete==2.0.0
-contextlib2==0.6.0.post1
-distlib==0.3.6
-filelock==3.8.0
-future==0.18.2
-importlib-metadata==5.1.0
-importlib-resources==5.1.2
-netaddr==0.8.0
-netifaces==0.10.9
-verboselogs==1.7
-virtualenv==20.17.0
+appdirs==1.4.*
+argcomplete==2.0.*
+contextlib2==0.6.*
+distlib==0.3.*
+filelock==3.8.*
+future==0.18.*
+importlib-metadata==5.1.*
+importlib-resources==5.1.*
+netaddr==0.8.*
+netifaces==0.10.*
+verboselogs==1.7.*
+virtualenv==20.17.*

docker/tensorrt/Dockerfile.amd64

@@ -12,26 +12,11 @@ ARG TARGETARCH
 COPY docker/tensorrt/requirements-amd64.txt /requirements-tensorrt.txt
 RUN mkdir -p /trt-wheels && pip3 wheel --wheel-dir=/trt-wheels -r /requirements-tensorrt.txt
 
-# Build CuDNN
-FROM wget AS cudnn-deps
-
-ARG COMPUTE_LEVEL
-
-RUN apt-get update \
-    && apt-get install -y git build-essential
-
-RUN wget https://developer.download.nvidia.com/compute/cuda/repos/debian11/x86_64/cuda-keyring_1.1-1_all.deb \
-&& dpkg -i cuda-keyring_1.1-1_all.deb \
-&& apt-get update \
-&& apt-get -y install cuda-toolkit \
-&& rm -rf /var/lib/apt/lists/*
-
 FROM tensorrt-base AS frigate-tensorrt
 ENV TRT_VER=8.5.3
 RUN --mount=type=bind,from=trt-wheels,source=/trt-wheels,target=/deps/trt-wheels \
     pip3 install -U /deps/trt-wheels/*.whl && \
     ldconfig
-COPY --from=cudnn-deps /usr/local/cuda-12.6 /usr/local/cuda
 
 ENV LD_LIBRARY_PATH=/usr/local/lib/python3.9/dist-packages/tensorrt:/usr/local/cuda/lib64:/usr/local/lib/python3.9/dist-packages/nvidia/cufft/lib
 WORKDIR /opt/frigate/
@@ -42,7 +27,7 @@ FROM devcontainer AS devcontainer-trt
 
 COPY --from=trt-deps /usr/local/lib/libyolo_layer.so /usr/local/lib/libyolo_layer.so
 COPY --from=trt-deps /usr/local/src/tensorrt_demos /usr/local/src/tensorrt_demos
-COPY --from=cudnn-deps /usr/local/cuda-12.6 /usr/local/cuda
+COPY --from=trt-deps /usr/local/cuda-12.1 /usr/local/cuda
 COPY docker/tensorrt/detector/rootfs/ /
 COPY --from=trt-deps /usr/local/lib/libyolo_layer.so /usr/local/lib/libyolo_layer.so
 RUN --mount=type=bind,from=trt-wheels,source=/trt-wheels,target=/deps/trt-wheels \

docker/tensorrt/Dockerfile.base

@@ -24,6 +24,7 @@ ENV S6_CMD_WAIT_FOR_SERVICES_MAXTIME=0
 
 COPY --from=trt-deps /usr/local/lib/libyolo_layer.so /usr/local/lib/libyolo_layer.so
 COPY --from=trt-deps /usr/local/src/tensorrt_demos /usr/local/src/tensorrt_demos
+COPY --from=trt-deps /usr/local/cuda-12.* /usr/local/cuda
 COPY docker/tensorrt/detector/rootfs/ /
 ENV YOLO_MODELS=""
 

docs/docs/configuration/autotracking.md

@@ -41,6 +41,7 @@ cameras:
     ...
     onvif:
       # Required: host of the camera being connected to.
+      # NOTE: HTTP is assumed by default; HTTPS is supported if you specify the scheme, ex: "https://0.0.0.0".
       host: 0.0.0.0
       # Optional: ONVIF port for device (default: shown below).
       port: 8000
@@ -49,6 +50,8 @@ cameras:
       user: admin
       # Optional: password for login.
       password: admin
+      # Optional: Skip TLS verification from the ONVIF server (default: shown below)
+      tls_insecure: False
       # Optional: PTZ camera object autotracking. Keeps a moving object in
       # the center of the frame by automatically moving the PTZ camera.
       autotracking:

docs/docs/configuration/camera_specific.md

@@ -156,7 +156,9 @@ cameras:
 
 #### Reolink Doorbell
 
-The reolink doorbell supports 2-way audio via go2rtc and other applications. It is important that the http-flv stream is still used for stability, a secondary rtsp stream can be added that will be using for the two way audio only.
+The reolink doorbell supports two way audio via go2rtc and other applications. It is important that the http-flv stream is still used for stability, a secondary rtsp stream can be added that will be using for the two way audio only.
+
+Ensure HTTP is enabled in the camera's advanced network settings. To use two way talk with Frigate, see the [Live view documentation](/configuration/live#two-way-talk).
 
 ```yaml
 go2rtc:

docs/docs/configuration/genai.md

@@ -5,6 +5,8 @@ title: Generative AI
 
 Generative AI can be used to automatically generate descriptive text based on the thumbnails of your tracked objects. This helps with [Semantic Search](/configuration/semantic_search) in Frigate to provide more context about your tracked objects. Descriptions are accessed via the _Explore_ view in the Frigate UI by clicking on a tracked object's thumbnail.
 
+Requests for a description are sent off automatically to your AI provider at the end of the tracked object's lifecycle. Descriptions can also be regenerated manually via the Frigate UI.
+
 :::info
 
 Semantic Search must be enabled to use Generative AI.

docs/docs/configuration/index.md

@@ -203,14 +203,13 @@ detectors:
   ov:
     type: openvino
     device: AUTO
-    model:
-      path: /openvino-model/ssdlite_mobilenet_v2.xml
 
 model:
   width: 300
   height: 300
   input_tensor: nhwc
   input_pixel_format: bgr
+  path: /openvino-model/ssdlite_mobilenet_v2.xml
   labelmap_path: /openvino-model/coco_91cl_bkgr.txt
 
 record:

docs/docs/configuration/live.md

@@ -29,7 +29,7 @@ The default video and audio codec on your camera may not always be compatible wi
 
 ### Audio Support
 
-MSE Requires AAC audio, WebRTC requires PCMU/PCMA, or opus audio. If you want to support both MSE and WebRTC then your restream config needs to make sure both are enabled.
+MSE Requires PCMA/PCMU or AAC audio, WebRTC requires PCMA/PCMU or opus audio. If you want to support both MSE and WebRTC then your restream config needs to make sure both are enabled.
 
 ```yaml
 go2rtc:
@@ -138,3 +138,13 @@ services:
 :::
 
 See [go2rtc WebRTC docs](https://github.com/AlexxIT/go2rtc/tree/v1.8.3#module-webrtc) for more information about this.
+
+### Two way talk
+
+For devices that support two way talk, Frigate can be configured to use the feature from the camera's Live view in the Web UI. You should:
+
+- Set up go2rtc with [WebRTC](#webrtc-extra-configuration).
+- Ensure you access Frigate via https (may require [opening port 8971](/frigate/installation/#ports)).
+- For the Home Assistant Frigate card, [follow the docs](https://github.com/dermotduffy/frigate-hass-card?tab=readme-ov-file#using-2-way-audio) for the correct source.
+
+To use the Reolink Doorbell with two way talk, you should use the [recommended Reolink configuration](/configuration/camera_specific#reolink-doorbell)

docs/docs/configuration/object_detectors.md

@@ -144,7 +144,9 @@ detectors:
 
 #### SSDLite MobileNet v2
 
-An OpenVINO model is provided in the container at `/openvino-model/ssdlite_mobilenet_v2.xml` and is used by this detector type by default. The model comes from Intel's Open Model Zoo [SSDLite MobileNet V2](https://github.com/openvinotoolkit/open_model_zoo/tree/master/models/public/ssdlite_mobilenet_v2) and is converted to an FP16 precision IR model. Use the model configuration shown below when using the OpenVINO detector with the default model.
+An OpenVINO model is provided in the container at `/openvino-model/ssdlite_mobilenet_v2.xml` and is used by this detector type by default. The model comes from Intel's Open Model Zoo [SSDLite MobileNet V2](https://github.com/openvinotoolkit/open_model_zoo/tree/master/models/public/ssdlite_mobilenet_v2) and is converted to an FP16 precision IR model.
+
+Use the model configuration shown below when using the OpenVINO detector with the default OpenVINO model:
 
 ```yaml
 detectors:
@@ -254,6 +256,7 @@ yolov4x-mish-640
 yolov7-tiny-288
 yolov7-tiny-416
 yolov7-640
+yolov7-416
 yolov7-320
 yolov7x-640
 yolov7x-320
@@ -282,6 +285,8 @@ The TensorRT detector can be selected by specifying `tensorrt` as the model type
 
 The TensorRT detector uses `.trt` model files that are located in `/config/model_cache/tensorrt` by default. These model path and dimensions used will depend on which model you have generated.
 
+Use the config below to work with generated TRT models:
+
 ```yaml
 detectors:
   tensorrt:
@@ -501,11 +506,12 @@ detectors:
   cpu1:
     type: cpu
     num_threads: 3
-    model:
-      path: "/custom_model.tflite"
   cpu2:
     type: cpu
     num_threads: 3
+
+model:
+  path: "/custom_model.tflite"
 ```
 
 When using CPU detectors, you can add one CPU detector per camera. Adding more detectors than the number of cameras should not improve performance.
@@ -632,8 +638,6 @@ detectors:
   hailo8l:
     type: hailo8l
     device: PCIe
-    model:
-      path: /config/model_cache/h8l_cache/ssd_mobilenet_v1.hef
 
 model:
   width: 300
@@ -641,4 +645,5 @@ model:
   input_tensor: nhwc
   input_pixel_format: bgr
   model_type: ssd
+  path: /config/model_cache/h8l_cache/ssd_mobilenet_v1.hef
 ```

docs/docs/configuration/reference.md

@@ -52,7 +52,7 @@ detectors:
   # Required: name of the detector
   detector_name:
     # Required: type of the detector
-    # Frigate provided types include 'cpu', 'edgetpu', 'openvino' and 'tensorrt' (default: shown below)
+    # Frigate provides many types, see https://docs.frigate.video/configuration/object_detectors for more details (default: shown below)
     # Additional detector types can also be plugged in.
     # Detectors may require additional configuration.
     # Refer to the Detectors configuration page for more information.
@@ -117,25 +117,27 @@ auth:
   hash_iterations: 600000
 
 # Optional: model modifications
+# NOTE: The default values are for the EdgeTPU detector.
+# Other detectors will require the model config to be set.
 model:
-  # Optional: path to the model (default: automatic based on detector)
+  # Required: path to the model (default: automatic based on detector)
   path: /edgetpu_model.tflite
-  # Optional: path to the labelmap (default: shown below)
+  # Required: path to the labelmap (default: shown below)
   labelmap_path: /labelmap.txt
   # Required: Object detection model input width (default: shown below)
   width: 320
   # Required: Object detection model input height (default: shown below)
   height: 320
-  # Optional: Object detection model input colorspace
+  # Required: Object detection model input colorspace
   # Valid values are rgb, bgr, or yuv. (default: shown below)
   input_pixel_format: rgb
-  # Optional: Object detection model input tensor format
+  # Required: Object detection model input tensor format
   # Valid values are nhwc or nchw (default: shown below)
   input_tensor: nhwc
-  # Optional: Object detection model type, currently only used with the OpenVINO detector
+  # Required: Object detection model type, currently only used with the OpenVINO detector
   # Valid values are ssd, yolox, yolonas (default: shown below)
   model_type: ssd
-  # Optional: Label name modifications. These are merged into the standard labelmap.
+  # Required: Label name modifications. These are merged into the standard labelmap.
   labelmap:
     2: vehicle
   # Optional: Map of object labels to their attribute labels (default: depends on model)
@@ -686,6 +688,7 @@ cameras:
     # to enable PTZ controls.
     onvif:
       # Required: host of the camera being connected to.
+      # NOTE: HTTP is assumed by default; HTTPS is supported if you specify the scheme, ex: "https://0.0.0.0".
       host: 0.0.0.0
       # Optional: ONVIF port for device (default: shown below).
       port: 8000
@@ -694,6 +697,8 @@ cameras:
       user: admin
       # Optional: password for login.
       password: admin
+      # Optional: Skip TLS verification from the ONVIF server (default: shown below)
+      tls_insecure: False
       # Optional: Ignores time synchronization mismatches between the camera and the server during authentication.
       # Using NTP on both ends is recommended and this should only be set to True in a "safe" environment due to the security risk it represents.
       ignore_time_mismatch: False
@@ -757,6 +762,8 @@ cameras:
         - cat
       # Optional: Restrict generation to objects that entered any of the listed zones (default: none, all zones qualify)
       required_zones: []
+      # Optional: Save thumbnails sent to generative AI for review/debugging purposes (default: shown below)
+      debug_save_thumbnails: False
 
 # Optional
 ui:

docs/docs/frigate/installation.md

@@ -305,8 +305,15 @@ To install make sure you have the [community app plugin here](https://forums.unr
 
 ## Proxmox
 
-It is recommended to run Frigate in LXC, rather than in a VM, for maximum performance. The setup can be complex so be prepared to read the Proxmox and LXC documentation. Suggestions include:
+[According to Proxmox documentation](https://pve.proxmox.com/pve-docs/pve-admin-guide.html#chapter_pct) it is recommended that you run application containers like Frigate inside a Proxmox QEMU VM. This will give you all the advantages of application containerization, while also providing the benefits that VMs offer, such as strong isolation from the host and the ability to live-migrate, which otherwise isn’t possible with containers.
 
+:::warning
+
+If you choose to run Frigate via LXC in Proxmox the setup can be complex so be prepared to read the Proxmox and LXC documentation, Frigate does not officially support running inside of an LXC.
+
+:::
+
+ Suggestions include:
 - For Intel-based hardware acceleration, to allow access to the `/dev/dri/renderD128` device with major number 226 and minor number 128, add the following lines to the `/etc/pve/lxc/<id>.conf` LXC configuration:
   - `lxc.cgroup2.devices.allow: c 226:128 rwm`
   - `lxc.mount.entry: /dev/dri/renderD128 dev/dri/renderD128 none bind,optional,create=file`

docs/docs/troubleshooting/recordings.md

@@ -3,7 +3,15 @@ id: recordings
 title: Troubleshooting Recordings
 ---
 
-### WARNING : Unable to keep up with recording segments in cache for camera. Keeping the 5 most recent segments out of 6 and discarding the rest...
+## I have Frigate configured for motion recording only, but it still seems to be recording even with no motion. Why?
+
+You'll want to:
+
+- Make sure your camera's timestamp is masked out with a motion mask. Even if there is no motion occurring in your scene, your motion settings may be sensitive enough to count your timestamp as motion.
+- If you have audio detection enabled, keep in mind that audio that is heard above `min_volume` is considered motion.
+- [Tune your motion detection settings](/configuration/motion_detection) either by editing your config file or by using the UI's Motion Tuner.
+
+## I see the message: WARNING : Unable to keep up with recording segments in cache for camera. Keeping the 5 most recent segments out of 6 and discarding the rest...
 
 This error can be caused by a number of different issues. The first step in troubleshooting is to enable debug logging for recording. This will enable logging showing how long it takes for recordings to be moved from RAM cache to the disk.
 
@@ -40,6 +48,7 @@ On linux, some helpful tools/commands in diagnosing would be:
 On modern linux kernels, the system will utilize some swap if enabled. Setting vm.swappiness=1 no longer means that the kernel will only swap in order to avoid OOM. To prevent any swapping inside a container, set allocations memory and memory+swap to be the same and disable swapping by setting the following docker/podman run parameters:
 
 **Compose example**
+
 ```yaml
 version: "3.9"
 services:
@@ -54,6 +63,7 @@ services:
 ```
 
 **Run command example**
+
 ```
 --memory=<MAXRAM> --memory-swap=<MAXSWAP> --memory-swappiness=0
 ```

docs/package.json

@@ -17,15 +17,15 @@
     "write-heading-ids": "docusaurus write-heading-ids"
   },
   "dependencies": {
-    "@docusaurus/core": "^3.5.2",
-    "@docusaurus/preset-classic": "^3.5.2",
-    "@docusaurus/theme-mermaid": "^3.5.2",
-    "@docusaurus/plugin-content-docs": "^3.5.2",
-    "@mdx-js/react": "^3.0.1",
+    "@docusaurus/core": "^3.6.3",
+    "@docusaurus/preset-classic": "^3.6.3",
+    "@docusaurus/theme-mermaid": "^3.6.3",
+    "@docusaurus/plugin-content-docs": "^3.6.3",
+    "@mdx-js/react": "^3.1.0",
     "clsx": "^2.1.1",
-    "docusaurus-plugin-openapi-docs": "^4.1.0",
-    "docusaurus-theme-openapi-docs": "^4.1.0",
-    "prism-react-renderer": "^2.4.0",
+    "docusaurus-plugin-openapi-docs": "^4.3.1",
+    "docusaurus-theme-openapi-docs": "^4.3.1",
+    "prism-react-renderer": "^2.4.1",
     "raw-loader": "^4.0.2",
     "react": "^18.3.1",
     "react-dom": "^18.3.1"

frigate/api/app.py

@@ -139,6 +139,8 @@ def config(request: Request):
         mode="json", warnings="none", exclude_none=True
     )
     for stream_name, stream in go2rtc.get("streams", {}).items():
+        if stream is None:
+            continue
         if isinstance(stream, str):
             cleaned = clean_camera_user_pass(stream)
         else:

frigate/app.py

@@ -437,7 +437,7 @@ class FrigateApp:
             # pre-create shms
             for i in range(shm_frame_count):
                 frame_size = config.frame_shape_yuv[0] * config.frame_shape_yuv[1]
-                self.frame_manager.create(f"{config.name}_{i}", frame_size)
+                self.frame_manager.create(f"{config.name}_frame{i}", frame_size)
 
             capture_process = util.Process(
                 target=capture_camera,

frigate/comms/webpush.py

@@ -151,7 +151,7 @@ class WebPushClient(Communicator):  # type: ignore[misc]
         camera: str = payload["after"]["camera"]
         title = f"{', '.join(sorted_objects).replace('_', ' ').title()}{' was' if state == 'end' else ''} detected in {', '.join(payload['after']['data']['zones']).replace('_', ' ').title()}"
         message = f"Detected on {camera.replace('_', ' ').title()}"
-        image = f'{payload["after"]["thumb_path"].replace("/media/frigate", "")}'
+        image = f"{payload['after']['thumb_path'].replace('/media/frigate', '')}"
 
         # if event is ongoing open to live view otherwise open to recordings view
         direct_url = f"/review?id={reviewId}" if state == "end" else f"/#{camera}"

frigate/config/camera/genai.py

@@ -38,6 +38,10 @@ class GenAICameraConfig(BaseModel):
         default_factory=list,
         title="List of required zones to be entered in order to run generative AI.",
     )
+    debug_save_thumbnails: bool = Field(
+        default=False,
+        title="Save thumbnails sent to generative AI for debugging purposes.",
+    )
 
     @field_validator("required_zones", mode="before")
     @classmethod

frigate/config/camera/onvif.py

@@ -74,6 +74,7 @@ class OnvifConfig(FrigateBaseModel):
     port: int = Field(default=8000, title="Onvif Port")
     user: Optional[EnvString] = Field(default=None, title="Onvif Username")
     password: Optional[EnvString] = Field(default=None, title="Onvif Password")
+    tls_insecure: bool = Field(default=False, title="Onvif Disable TLS verification")
     autotracking: PtzAutotrackConfig = Field(
         default_factory=PtzAutotrackConfig,
         title="PTZ auto tracking config.",

frigate/config/camera/record.py

@@ -4,6 +4,7 @@ from typing import Optional
 from pydantic import Field
 
 from frigate.const import MAX_PRE_CAPTURE
+from frigate.review.types import SeverityEnum
 
 from ..base import FrigateBaseModel
 
@@ -101,3 +102,15 @@ class RecordConfig(FrigateBaseModel):
             self.alerts.pre_capture,
             self.detections.pre_capture,
         )
+
+    def get_review_pre_capture(self, severity: SeverityEnum) -> int:
+        if severity == SeverityEnum.alert:
+            return self.alerts.pre_capture
+        else:
+            return self.detections.pre_capture
+
+    def get_review_post_capture(self, severity: SeverityEnum) -> int:
+        if severity == SeverityEnum.alert:
+            return self.alerts.post_capture
+        else:
+            return self.detections.post_capture

frigate/config/camera/zone.py

@@ -85,7 +85,7 @@ class ZoneConfig(BaseModel):
             if explicit:
                 self.coordinates = ",".join(
                     [
-                        f'{round(int(p.split(",")[0]) / frame_shape[1], 3)},{round(int(p.split(",")[1]) / frame_shape[0], 3)}'
+                        f"{round(int(p.split(',')[0]) / frame_shape[1], 3)},{round(int(p.split(',')[1]) / frame_shape[0], 3)}"
                         for p in coordinates
                     ]
                 )

frigate/config/config.py

@@ -594,35 +594,27 @@ class FrigateConfig(FrigateBaseModel):
                 if isinstance(detector, dict)
                 else detector.model_dump(warnings="none")
             )
-            detector_config: DetectorConfig = adapter.validate_python(model_dict)
-            if detector_config.model is None:
-                detector_config.model = self.model.model_copy()
-            else:
-                path = detector_config.model.path
-                detector_config.model = self.model.model_copy()
-                detector_config.model.path = path
+            detector_config: BaseDetectorConfig = adapter.validate_python(model_dict)
 
-                if "path" not in model_dict or len(model_dict.keys()) > 1:
-                    logger.warning(
-                        "Customizing more than a detector model path is unsupported."
-                    )
+            # users should not set model themselves
+            if detector_config.model:
+                detector_config.model = None
 
-            merged_model = deep_merge(
-                detector_config.model.model_dump(exclude_unset=True, warnings="none"),
-                self.model.model_dump(exclude_unset=True, warnings="none"),
-            )
+            model_config = self.model.model_dump(exclude_unset=True, warnings="none")
 
-            if "path" not in merged_model:
+            if detector_config.model_path:
+                model_config["path"] = detector_config.model_path
+
+            if "path" not in model_config:
                 if detector_config.type == "cpu":
-                    merged_model["path"] = "/cpu_model.tflite"
+                    model_config["path"] = "/cpu_model.tflite"
                 elif detector_config.type == "edgetpu":
-                    merged_model["path"] = "/edgetpu_model.tflite"
+                    model_config["path"] = "/edgetpu_model.tflite"
 
-            detector_config.model = ModelConfig.model_validate(merged_model)
-            detector_config.model.check_and_load_plus_model(
-                self.plus_api, detector_config.type
-            )
-            detector_config.model.compute_model_hash()
+            model = ModelConfig.model_validate(model_config)
+            model.check_and_load_plus_model(self.plus_api, detector_config.type)
+            model.compute_model_hash()
+            detector_config.model = model
             self.detectors[key] = detector_config
 
         return self

frigate/detectors/detector_config.py

@@ -194,6 +194,9 @@ class BaseDetectorConfig(BaseModel):
     model: Optional[ModelConfig] = Field(
         default=None, title="Detector specific model configuration."
     )
+    model_path: Optional[str] = Field(
+        default=None, title="Detector specific model path."
+    )
     model_config = ConfigDict(
         extra="allow", arbitrary_types_allowed=True, protected_namespaces=()
     )

frigate/detectors/plugins/tensorrt.py

@@ -219,19 +219,19 @@ class TensorRtDetector(DetectionApi):
         ]
 
     def __init__(self, detector_config: TensorRTDetectorConfig):
-        assert (
-            TRT_SUPPORT
-        ), f"TensorRT libraries not found, {DETECTOR_KEY} detector not present"
+        assert TRT_SUPPORT, (
+            f"TensorRT libraries not found, {DETECTOR_KEY} detector not present"
+        )
 
         (cuda_err,) = cuda.cuInit(0)
-        assert (
-            cuda_err == cuda.CUresult.CUDA_SUCCESS
-        ), f"Failed to initialize cuda {cuda_err}"
+        assert cuda_err == cuda.CUresult.CUDA_SUCCESS, (
+            f"Failed to initialize cuda {cuda_err}"
+        )
         err, dev_count = cuda.cuDeviceGetCount()
         logger.debug(f"Num Available Devices: {dev_count}")
-        assert (
-            detector_config.device < dev_count
-        ), f"Invalid TensorRT Device Config. Device {detector_config.device} Invalid."
+        assert detector_config.device < dev_count, (
+            f"Invalid TensorRT Device Config. Device {detector_config.device} Invalid."
+        )
         err, self.cu_ctx = cuda.cuCtxCreate(
             cuda.CUctx_flags.CU_CTX_MAP_HOST, detector_config.device
         )

frigate/embeddings/maintainer.py

@@ -5,6 +5,7 @@ import logging
 import os
 import threading
 from multiprocessing.synchronize import Event as MpEvent
+from pathlib import Path
 from typing import Optional
 
 import cv2
@@ -217,16 +218,47 @@ class EmbeddingMaintainer(threading.Thread):
                             _, buffer = cv2.imencode(".jpg", cropped_image)
                             snapshot_image = buffer.tobytes()
 
+                    num_thumbnails = len(self.tracked_events.get(event_id, []))
+
                     embed_image = (
                         [snapshot_image]
                         if event.has_snapshot and camera_config.genai.use_snapshot
                         else (
-                            [thumbnail for data in self.tracked_events[event_id]]
-                            if len(self.tracked_events.get(event_id, [])) > 0
+                            [
+                                data["thumbnail"]
+                                for data in self.tracked_events[event_id]
+                            ]
+                            if num_thumbnails > 0
                             else [thumbnail]
                         )
                     )
 
+                    if camera_config.genai.debug_save_thumbnails and num_thumbnails > 0:
+                        logger.debug(
+                            f"Saving {num_thumbnails} thumbnails for event {event.id}"
+                        )
+
+                        Path(
+                            os.path.join(CLIPS_DIR, f"genai-requests/{event.id}")
+                        ).mkdir(parents=True, exist_ok=True)
+
+                        for idx, data in enumerate(self.tracked_events[event_id], 1):
+                            jpg_bytes: bytes = data["thumbnail"]
+
+                            if jpg_bytes is None:
+                                logger.warning(
+                                    f"Unable to save thumbnail {idx} for {event.id}."
+                                )
+                            else:
+                                with open(
+                                    os.path.join(
+                                        CLIPS_DIR,
+                                        f"genai-requests/{event.id}/{idx}.jpg",
+                                    ),
+                                    "wb",
+                                ) as j:
+                                    j.write(jpg_bytes)
+
                     # Generate the description. Call happens in a thread since it is network bound.
                     threading.Thread(
                         target=self._embed_description,
@@ -357,7 +389,7 @@ class EmbeddingMaintainer(threading.Thread):
             [snapshot_image]
             if event.has_snapshot and source == "snapshot"
             else (
-                [thumbnail for data in self.tracked_events[event_id]]
+                [data["thumbnail"] for data in self.tracked_events[event_id]]
                 if len(self.tracked_events.get(event_id, [])) > 0
                 else [thumbnail]
             )

frigate/events/cleanup.py

@@ -121,8 +121,8 @@ class EventCleanup(threading.Thread):
 
             events_to_update = []
 
-            for batch in query.iterator():
-                events_to_update.extend([event.id for event in batch])
+            for event in query.iterator():
+                events_to_update.append(event.id)
                 if len(events_to_update) >= CHUNK_SIZE:
                     logger.debug(
                         f"Updating {update_params} for {len(events_to_update)} events"
@@ -257,7 +257,7 @@ class EventCleanup(threading.Thread):
         events_to_update = []
 
         for event in query.iterator():
-            events_to_update.append(event)
+            events_to_update.append(event.id)
 
             if len(events_to_update) >= CHUNK_SIZE:
                 logger.debug(

frigate/ffmpeg_presets.py

@@ -71,8 +71,8 @@ PRESETS_HW_ACCEL_DECODE = {
     "preset-rpi-64-h264": "-c:v:1 h264_v4l2m2m",
     "preset-rpi-64-h265": "-c:v:1 hevc_v4l2m2m",
     FFMPEG_HWACCEL_VAAPI: f"-hwaccel_flags allow_profile_mismatch -hwaccel vaapi -hwaccel_device {_gpu_selector.get_selected_gpu()} -hwaccel_output_format vaapi",
-    "preset-intel-qsv-h264": f"-hwaccel qsv -qsv_device {_gpu_selector.get_selected_gpu()} -hwaccel_output_format qsv -c:v h264_qsv",
-    "preset-intel-qsv-h265": f"-load_plugin hevc_hw -hwaccel qsv -qsv_device {_gpu_selector.get_selected_gpu()} -hwaccel_output_format qsv -c:v hevc_qsv",
+    "preset-intel-qsv-h264": f"-hwaccel qsv -qsv_device {_gpu_selector.get_selected_gpu()} -hwaccel_output_format qsv -c:v h264_qsv -bsf:v dump_extra",  # https://trac.ffmpeg.org/ticket/9766#comment:17
+    "preset-intel-qsv-h265": f"-load_plugin hevc_hw -hwaccel qsv -qsv_device {_gpu_selector.get_selected_gpu()} -hwaccel_output_format qsv -c:v hevc_qsv -bsf:v dump_extra",  # https://trac.ffmpeg.org/ticket/9766#comment:17
     FFMPEG_HWACCEL_NVIDIA: "-hwaccel cuda -hwaccel_output_format cuda",
     "preset-jetson-h264": "-c:v h264_nvmpi -resize {1}x{2}",
     "preset-jetson-h265": "-c:v hevc_nvmpi -resize {1}x{2}",

frigate/plus.py

@@ -68,11 +68,13 @@ class PlusApi:
             or self._token_data["expires"] - datetime.datetime.now().timestamp() < 60
         ):
             if self.key is None:
-                raise Exception("Plus API not activated")
+                raise Exception(
+                    "Plus API key not set. See https://docs.frigate.video/integrations/plus#set-your-api-key"
+                )
             parts = self.key.split(":")
             r = requests.get(f"{self.host}/v1/auth/token", auth=(parts[0], parts[1]))
             if not r.ok:
-                raise Exception("Unable to refresh API token")
+                raise Exception(f"Unable to refresh API token: {r.text}")
             self._token_data = r.json()
 
     def _get_authorization_header(self) -> dict:
@@ -116,15 +118,6 @@ class PlusApi:
             logger.error(f"Failed to upload original: {r.status_code} {r.text}")
             raise Exception(r.text)
 
-        # resize and submit annotate
-        files = {"file": get_jpg_bytes(image, 640, 70)}
-        data = presigned_urls["annotate"]["fields"]
-        data["content-type"] = "image/jpeg"
-        r = requests.post(presigned_urls["annotate"]["url"], files=files, data=data)
-        if not r.ok:
-            logger.error(f"Failed to upload annotate: {r.status_code} {r.text}")
-            raise Exception(r.text)
-
         # resize and submit thumbnail
         files = {"file": get_jpg_bytes(image, 200, 70)}
         data = presigned_urls["thumbnail"]["fields"]

frigate/ptz/autotrack.py

@@ -135,7 +135,7 @@ class PtzMotionEstimator:
 
             try:
                 logger.debug(
-                    f"{camera}: Motion estimator transformation: {self.coord_transformations.rel_to_abs([[0,0]])}"
+                    f"{camera}: Motion estimator transformation: {self.coord_transformations.rel_to_abs([[0, 0]])}"
                 )
             except Exception:
                 pass
@@ -471,7 +471,7 @@ class PtzAutoTracker:
                 self.onvif.get_camera_status(camera)
 
             logger.info(
-                f"Calibration for {camera} in progress: {round((step/num_steps)*100)}% complete"
+                f"Calibration for {camera} in progress: {round((step / num_steps) * 100)}% complete"
             )
 
         self.calibrating[camera] = False
@@ -690,7 +690,7 @@ class PtzAutoTracker:
                             f"{camera}: Predicted movement time: {self._predict_movement_time(camera, pan, tilt)}"
                         )
                         logger.debug(
-                            f"{camera}: Actual movement time: {self.ptz_metrics[camera].stop_time.value-self.ptz_metrics[camera].start_time.value}"
+                            f"{camera}: Actual movement time: {self.ptz_metrics[camera].stop_time.value - self.ptz_metrics[camera].start_time.value}"
                         )
 
                     # save metrics for better estimate calculations
@@ -983,10 +983,10 @@ class PtzAutoTracker:
             logger.debug(f"{camera}: Zoom test: at max zoom: {at_max_zoom}")
             logger.debug(f"{camera}: Zoom test: at min zoom: {at_min_zoom}")
             logger.debug(
-                f'{camera}: Zoom test: zoom in hysteresis limit: {zoom_in_hysteresis} value: {AUTOTRACKING_ZOOM_IN_HYSTERESIS} original: {self.tracked_object_metrics[camera]["original_target_box"]} max: {self.tracked_object_metrics[camera]["max_target_box"]} target: {calculated_target_box if calculated_target_box else self.tracked_object_metrics[camera]["target_box"]}'
+                f"{camera}: Zoom test: zoom in hysteresis limit: {zoom_in_hysteresis} value: {AUTOTRACKING_ZOOM_IN_HYSTERESIS} original: {self.tracked_object_metrics[camera]['original_target_box']} max: {self.tracked_object_metrics[camera]['max_target_box']} target: {calculated_target_box if calculated_target_box else self.tracked_object_metrics[camera]['target_box']}"
             )
             logger.debug(
-                f'{camera}: Zoom test: zoom out hysteresis limit: {zoom_out_hysteresis} value: {AUTOTRACKING_ZOOM_OUT_HYSTERESIS} original: {self.tracked_object_metrics[camera]["original_target_box"]} max: {self.tracked_object_metrics[camera]["max_target_box"]} target: {calculated_target_box if calculated_target_box else self.tracked_object_metrics[camera]["target_box"]}'
+                f"{camera}: Zoom test: zoom out hysteresis limit: {zoom_out_hysteresis} value: {AUTOTRACKING_ZOOM_OUT_HYSTERESIS} original: {self.tracked_object_metrics[camera]['original_target_box']} max: {self.tracked_object_metrics[camera]['max_target_box']} target: {calculated_target_box if calculated_target_box else self.tracked_object_metrics[camera]['target_box']}"
             )
 
         # Zoom in conditions (and)
@@ -1069,7 +1069,7 @@ class PtzAutoTracker:
                 pan = ((centroid_x / camera_width) - 0.5) * 2
                 tilt = (0.5 - (centroid_y / camera_height)) * 2
 
-            logger.debug(f'{camera}: Original box: {obj.obj_data["box"]}')
+            logger.debug(f"{camera}: Original box: {obj.obj_data['box']}")
             logger.debug(f"{camera}: Predicted box: {tuple(predicted_box)}")
             logger.debug(
                 f"{camera}: Velocity: {tuple(np.round(average_velocity).flatten().astype(int))}"
@@ -1179,7 +1179,7 @@ class PtzAutoTracker:
                     )
                     zoom = (ratio - 1) / (ratio + 1)
                     logger.debug(
-                        f'{camera}: limit: {self.tracked_object_metrics[camera]["max_target_box"]}, ratio: {ratio} zoom calculation: {zoom}'
+                        f"{camera}: limit: {self.tracked_object_metrics[camera]['max_target_box']}, ratio: {ratio} zoom calculation: {zoom}"
                     )
                     if not result:
                         # zoom out with special condition if zooming out because of velocity, edges, etc.

frigate/ptz/onvif.py

@@ -6,6 +6,7 @@ from importlib.util import find_spec
 from pathlib import Path
 
 import numpy
+import requests
 from onvif import ONVIFCamera, ONVIFError
 from zeep.exceptions import Fault, TransportError
 from zeep.transports import Transport
@@ -48,7 +49,11 @@ class OnvifController:
 
             if cam.onvif.host:
                 try:
-                    transport = Transport(timeout=10, operation_timeout=10)
+                    session = requests.Session()
+                    session.verify = not cam.onvif.tls_insecure
+                    transport = Transport(
+                        timeout=10, operation_timeout=10, session=session
+                    )
                     self.cams[cam_name] = {
                         "onvif": ONVIFCamera(
                             cam.onvif.host,
@@ -558,22 +563,26 @@ class OnvifController:
             if not self._init_onvif(camera_name):
                 return
 
-        if command == OnvifCommandEnum.init:
-            # already init
-            return
-        elif command == OnvifCommandEnum.stop:
-            self._stop(camera_name)
-        elif command == OnvifCommandEnum.preset:
-            self._move_to_preset(camera_name, param)
-        elif command == OnvifCommandEnum.move_relative:
-            _, pan, tilt = param.split("_")
-            self._move_relative(camera_name, float(pan), float(tilt), 0, 1)
-        elif (
-            command == OnvifCommandEnum.zoom_in or command == OnvifCommandEnum.zoom_out
-        ):
-            self._zoom(camera_name, command)
-        else:
-            self._move(camera_name, command)
+        try:
+            if command == OnvifCommandEnum.init:
+                # already init
+                return
+            elif command == OnvifCommandEnum.stop:
+                self._stop(camera_name)
+            elif command == OnvifCommandEnum.preset:
+                self._move_to_preset(camera_name, param)
+            elif command == OnvifCommandEnum.move_relative:
+                _, pan, tilt = param.split("_")
+                self._move_relative(camera_name, float(pan), float(tilt), 0, 1)
+            elif (
+                command == OnvifCommandEnum.zoom_in
+                or command == OnvifCommandEnum.zoom_out
+            ):
+                self._zoom(camera_name, command)
+            else:
+                self._move(camera_name, command)
+        except ONVIFError as e:
+            logger.error(f"Unable to handle onvif command: {e}")
 
     def get_camera_info(self, camera_name: str) -> dict[str, any]:
         if camera_name not in self.cams.keys():

frigate/record/maintainer.py

@@ -29,6 +29,7 @@ from frigate.const import (
     RECORD_DIR,
 )
 from frigate.models import Recordings, ReviewSegment
+from frigate.review.types import SeverityEnum
 from frigate.util.services import get_video_properties
 
 logger = logging.getLogger(__name__)
@@ -194,6 +195,7 @@ class RecordingMaintainer(threading.Thread):
                 ReviewSegment.select(
                     ReviewSegment.start_time,
                     ReviewSegment.end_time,
+                    ReviewSegment.severity,
                     ReviewSegment.data,
                 )
                 .where(
@@ -219,11 +221,15 @@ class RecordingMaintainer(threading.Thread):
             [r for r in recordings_to_insert if r is not None],
         )
 
+    def drop_segment(self, cache_path: str) -> None:
+        Path(cache_path).unlink(missing_ok=True)
+        self.end_time_cache.pop(cache_path, None)
+
     async def validate_and_move_segment(
         self, camera: str, reviews: list[ReviewSegment], recording: dict[str, any]
     ) -> None:
-        cache_path = recording["cache_path"]
-        start_time = recording["start_time"]
+        cache_path: str = recording["cache_path"]
+        start_time: datetime.datetime = recording["start_time"]
         record_config = self.config.cameras[camera].record
 
         # Just delete files if recordings are turned off
@@ -231,8 +237,7 @@ class RecordingMaintainer(threading.Thread):
             camera not in self.config.cameras
             or not self.config.cameras[camera].record.enabled
         ):
-            Path(cache_path).unlink(missing_ok=True)
-            self.end_time_cache.pop(cache_path, None)
+            self.drop_segment(cache_path)
             return
 
         if cache_path in self.end_time_cache:
@@ -260,24 +265,34 @@ class RecordingMaintainer(threading.Thread):
                 return
 
         # if cached file's start_time is earlier than the retain days for the camera
+        # meaning continuous recording is not enabled
         if start_time <= (
             datetime.datetime.now().astimezone(datetime.timezone.utc)
             - datetime.timedelta(days=self.config.cameras[camera].record.retain.days)
         ):
-            # if the cached segment overlaps with the events:
+            # if the cached segment overlaps with the review items:
             overlaps = False
             for review in reviews:
-                # if the event starts in the future, stop checking events
+                severity = SeverityEnum[review.severity]
+
+                # if the review item starts in the future, stop checking review items
                 # and remove this segment
-                if review.start_time > end_time.timestamp():
+                if (
+                    review.start_time - record_config.get_review_pre_capture(severity)
+                ) > end_time.timestamp():
                     overlaps = False
-                    Path(cache_path).unlink(missing_ok=True)
-                    self.end_time_cache.pop(cache_path, None)
                     break
 
-                # if the event is in progress or ends after the recording starts, keep it
-                # and stop looking at events
-                if review.end_time is None or review.end_time >= start_time.timestamp():
+                # if the review item is in progress or ends after the recording starts, keep it
+                # and stop looking at review items
+                if (
+                    review.end_time is None
+                    or (
+                        review.end_time
+                        + record_config.get_review_post_capture(severity)
+                    )
+                    >= start_time.timestamp()
+                ):
                     overlaps = True
                     break
 
@@ -296,7 +311,7 @@ class RecordingMaintainer(threading.Thread):
                     cache_path,
                     record_mode,
                 )
-            # if it doesn't overlap with an event, go ahead and drop the segment
+            # if it doesn't overlap with an review item, go ahead and drop the segment
             # if it ends more than the configured pre_capture for the camera
             else:
                 camera_info = self.object_recordings_info[camera]
@@ -307,9 +322,9 @@ class RecordingMaintainer(threading.Thread):
                     most_recently_processed_frame_time - record_config.event_pre_capture
                 ).astimezone(datetime.timezone.utc)
                 if end_time < retain_cutoff:
-                    Path(cache_path).unlink(missing_ok=True)
-                    self.end_time_cache.pop(cache_path, None)
+                    self.drop_segment(cache_path)
         # else retain days includes this segment
+        # meaning continuous recording is enabled
         else:
             # assume that empty means the relevant recording info has not been received yet
             camera_info = self.object_recordings_info[camera]
@@ -390,8 +405,7 @@ class RecordingMaintainer(threading.Thread):
 
         # check if the segment shouldn't be stored
         if segment_info.should_discard_segment(store_mode):
-            Path(cache_path).unlink(missing_ok=True)
-            self.end_time_cache.pop(cache_path, None)
+            self.drop_segment(cache_path)
             return
 
         # directory will be in utc due to start_time being in utc
@@ -435,7 +449,7 @@ class RecordingMaintainer(threading.Thread):
                     return None
                 else:
                     logger.debug(
-                        f"Copied {file_path} in {datetime.datetime.now().timestamp()-start_frame} seconds."
+                        f"Copied {file_path} in {datetime.datetime.now().timestamp() - start_frame} seconds."
                     )
 
                 try:

frigate/review/maintainer.py

@@ -256,7 +256,7 @@ class ReviewSegmentMaintainer(threading.Thread):
                 elif object["sub_label"][0] in self.config.model.all_attributes:
                     segment.detections[object["id"]] = object["sub_label"][0]
                 else:
-                    segment.detections[object["id"]] = f'{object["label"]}-verified'
+                    segment.detections[object["id"]] = f"{object['label']}-verified"
                     segment.sub_labels[object["id"]] = object["sub_label"][0]
 
                 # if object is alert label
@@ -352,7 +352,7 @@ class ReviewSegmentMaintainer(threading.Thread):
                 elif object["sub_label"][0] in self.config.model.all_attributes:
                     detections[object["id"]] = object["sub_label"][0]
                 else:
-                    detections[object["id"]] = f'{object["label"]}-verified'
+                    detections[object["id"]] = f"{object['label']}-verified"
                     sub_labels[object["id"]] = object["sub_label"][0]
 
                 # if object is alert label
@@ -527,7 +527,9 @@ class ReviewSegmentMaintainer(threading.Thread):
 
                         if event_id in self.indefinite_events[camera]:
                             self.indefinite_events[camera].pop(event_id)
-                            current_segment.last_update = manual_info["end_time"]
+
+                            if len(self.indefinite_events[camera]) == 0:
+                                current_segment.last_update = manual_info["end_time"]
                         else:
                             logger.error(
                                 f"Event with ID {event_id} has a set duration and can not be ended manually."

frigate/service_manager/multiprocessing.py

@@ -72,8 +72,7 @@ class BaseServiceProcess(Service, ABC):
                 running = False
             except TimeoutError:
                 self.manager.logger.warning(
-                    f"{self.name} is still running after "
-                    f"{timeout} seconds. Killing."
+                    f"{self.name} is still running after {timeout} seconds. Killing."
                 )
 
         if running:

frigate/stats/util.py

@@ -293,7 +293,7 @@ def stats_snapshot(
     for path in [RECORD_DIR, CLIPS_DIR, CACHE_DIR, "/dev/shm"]:
         try:
             storage_stats = shutil.disk_usage(path)
-        except FileNotFoundError:
+        except (FileNotFoundError, OSError):
             stats["service"]["storage"][path] = {}
             continue
 

frigate/test/test_config.py

@@ -75,11 +75,11 @@ class TestConfig(unittest.TestCase):
             "detectors": {
                 "cpu": {
                     "type": "cpu",
-                    "model": {"path": "/cpu_model.tflite"},
+                    "model_path": "/cpu_model.tflite",
                 },
                 "edgetpu": {
                     "type": "edgetpu",
-                    "model": {"path": "/edgetpu_model.tflite"},
+                    "model_path": "/edgetpu_model.tflite",
                 },
                 "openvino": {
                     "type": "openvino",

frigate/track/tracked_object.py

@@ -339,7 +339,7 @@ class TrackedObject:
                 box[2],
                 box[3],
                 self.obj_data["label"],
-                f"{int(self.thumbnail_data['score']*100)}% {int(self.thumbnail_data['area'])}",
+                f"{int(self.thumbnail_data['score'] * 100)}% {int(self.thumbnail_data['area'])}",
                 thickness=thickness,
                 color=color,
             )

frigate/util/config.py

@@ -13,7 +13,7 @@ from frigate.util.services import get_video_properties
 
 logger = logging.getLogger(__name__)
 
-CURRENT_CONFIG_VERSION = "0.15-0"
+CURRENT_CONFIG_VERSION = "0.15-1"
 DEFAULT_CONFIG_FILE = "/config/config.yml"
 
 
@@ -77,6 +77,13 @@ def migrate_frigate_config(config_file: str):
             yaml.dump(new_config, f)
         previous_version = "0.15-0"
 
+    if previous_version < "0.15-1":
+        logger.info(f"Migrating frigate config from {previous_version} to 0.15-1...")
+        new_config = migrate_015_1(config)
+        with open(config_file, "w") as f:
+            yaml.dump(new_config, f)
+        previous_version = "0.15-1"
+
     logger.info("Finished frigate config migration...")
 
 
@@ -267,6 +274,21 @@ def migrate_015_0(config: dict[str, dict[str, any]]) -> dict[str, dict[str, any]
     return new_config
 
 
+def migrate_015_1(config: dict[str, dict[str, any]]) -> dict[str, dict[str, any]]:
+    """Handle migrating frigate config to 0.15-1"""
+    new_config = config.copy()
+
+    for detector, detector_config in config.get("detectors", {}).items():
+        path = detector_config.get("model", {}).get("path")
+
+        if path:
+            new_config["detectors"][detector]["model_path"] = path
+            del new_config["detectors"][detector]["model"]
+
+    new_config["version"] = "0.15-1"
+    return new_config
+
+
 def get_relative_coordinates(
     mask: Optional[Union[str, list]], frame_shape: tuple[int, int]
 ) -> Union[str, list]:
@@ -292,7 +314,7 @@ def get_relative_coordinates(
                             continue
 
                         rel_points.append(
-                            f"{round(x / frame_shape[1], 3)},{round(y  / frame_shape[0], 3)}"
+                            f"{round(x / frame_shape[1], 3)},{round(y / frame_shape[0], 3)}"
                         )
 
                     relative_masks.append(",".join(rel_points))
@@ -315,7 +337,7 @@ def get_relative_coordinates(
                     return []
 
                 rel_points.append(
-                    f"{round(x / frame_shape[1], 3)},{round(y  / frame_shape[0], 3)}"
+                    f"{round(x / frame_shape[1], 3)},{round(y / frame_shape[0], 3)}"
                 )
 
             mask = ",".join(rel_points)

frigate/util/services.py

@@ -390,12 +390,22 @@ def try_get_info(f, h, default="N/A"):
 
 
 def get_nvidia_gpu_stats() -> dict[int, dict]:
+    names: dict[str, int] = {}
     results = {}
     try:
         nvml.nvmlInit()
         deviceCount = nvml.nvmlDeviceGetCount()
         for i in range(deviceCount):
             handle = nvml.nvmlDeviceGetHandleByIndex(i)
+            gpu_name = nvml.nvmlDeviceGetName(handle)
+
+            # handle case where user has multiple of same GPU
+            if gpu_name in names:
+                names[gpu_name] += 1
+                gpu_name += f" ({names.get(gpu_name)})"
+            else:
+                names[gpu_name] = 1
+
             meminfo = try_get_info(nvml.nvmlDeviceGetMemoryInfo, handle)
             util = try_get_info(nvml.nvmlDeviceGetUtilizationRates, handle)
             enc = try_get_info(nvml.nvmlDeviceGetEncoderUtilization, handle)
@@ -423,7 +433,7 @@ def get_nvidia_gpu_stats() -> dict[int, dict]:
                 dec_util = -1
 
             results[i] = {
-                "name": nvml.nvmlDeviceGetName(handle),
+                "name": gpu_name,
                 "gpu": gpu_util,
                 "mem": gpu_mem_util,
                 "enc": enc_util,

frigate/video.py

@@ -113,7 +113,7 @@ def capture_frames(
         fps.value = frame_rate.eps()
         skipped_fps.value = skipped_eps.eps()
         current_frame.value = datetime.datetime.now().timestamp()
-        frame_name = f"{config.name}_{frame_index}"
+        frame_name = f"{config.name}_frame{frame_index}"
         frame_buffer = frame_manager.write(frame_name)
         try:
             frame_buffer[:] = ffmpeg_process.stdout.read(frame_size)

process_clip.py

@@ -208,7 +208,7 @@ class ProcessClip:
                 box[2],
                 box[3],
                 obj["id"],
-                f"{int(obj['score']*100)}% {int(obj['area'])}",
+                f"{int(obj['score'] * 100)}% {int(obj['area'])}",
                 thickness=thickness,
                 color=color,
             )
@@ -227,7 +227,7 @@ class ProcessClip:
             )
 
         cv2.imwrite(
-            f"{os.path.join(debug_path, os.path.basename(self.clip_path))}.{int(frame_time*1000000)}.jpg",
+            f"{os.path.join(debug_path, os.path.basename(self.clip_path))}.{int(frame_time * 1000000)}.jpg",
             current_frame,
         )
 
@@ -290,7 +290,7 @@ def process(path, label, output, debug_path):
         1 for result in results if result[1]["true_positive_objects"] > 0
     )
     print(
-        f"Objects were detected in {positive_count}/{len(results)}({positive_count/len(results)*100:.2f}%) clip(s)."
+        f"Objects were detected in {positive_count}/{len(results)}({positive_count / len(results) * 100:.2f}%) clip(s)."
     )
 
     if output:

web/src/components/filter/CameraGroupSelector.tsx

@@ -755,7 +755,11 @@ export function CameraGroupEdit({
                 <FormMessage />
                 {[
                   ...(birdseyeConfig?.enabled ? ["birdseye"] : []),
-                  ...Object.keys(config?.cameras ?? {}),
+                  ...Object.keys(config?.cameras ?? {}).sort(
+                    (a, b) =>
+                      (config?.cameras[a]?.ui?.order ?? 0) -
+                      (config?.cameras[b]?.ui?.order ?? 0),
+                  ),
                 ].map((camera) => (
                   <FormControl key={camera}>
                     <FilterSwitch

web/src/components/overlay/detail/ObjectLifecycle.tsx

@@ -477,7 +477,10 @@ export default function ObjectLifecycle({
                           </p>
                           {Array.isArray(item.data.box) &&
                           item.data.box.length >= 4
-                            ? (item.data.box[2] / item.data.box[3]).toFixed(2)
+                            ? (
+                                aspectRatio *
+                                (item.data.box[2] / item.data.box[3])
+                              ).toFixed(2)
                             : "N/A"}
                         </div>
                       </div>

web/src/components/overlay/detail/ReviewDetailDialog.tsx

@@ -280,12 +280,24 @@ export default function ReviewDetailDialog({
               </div>
               {hasMismatch && (
                 <div className="p-4 text-center text-sm">
-                  Some objects may have been detected in this review item that
-                  did not qualify as an alert or detection. Adjust your
-                  configuration if you want Frigate to save tracked objects for
-                  any missing labels.
+                  {(() => {
+                    const detectedCount = Math.abs(
+                      (events?.length ?? 0) -
+                        (review?.data.detections.length ?? 0),
+                    );
+                    const objectLabel =
+                      detectedCount === 1 ? "object was" : "objects were";
+
+                    return `${detectedCount} unavailable ${objectLabel} detected and included in this review item.`;
+                  })()}{" "}
+                  Those objects either did not qualify as an alert or detection
+                  or have already been cleaned up/deleted.
                   {missingObjects.length > 0 && (
-                    <div className="mt-2">{missingObjects.join(", ")}</div>
+                    <div className="mt-2">
+                      Adjust your configuration if you want Frigate to save
+                      tracked objects for the following labels:{" "}
+                      {missingObjects.join(", ")}
+                    </div>
                   )}
                 </div>
               )}

web/src/components/overlay/detail/SearchDetailDialog.tsx

@@ -469,16 +469,43 @@ function ObjectDetailsTab({
         </div>
       </div>
       <div className="flex flex-col gap-1.5">
-        <div className="text-sm text-primary/40">Description</div>
-        <Textarea
-          className="h-64"
-          placeholder="Description of the tracked object"
-          value={desc}
-          onChange={(e) => setDesc(e.target.value)}
-        />
+        {config?.cameras[search.camera].genai.enabled &&
+        !search.end_time &&
+        (config.cameras[search.camera].genai.required_zones.length === 0 ||
+          search.zones.some((zone) =>
+            config.cameras[search.camera].genai.required_zones.includes(zone),
+          )) &&
+        (config.cameras[search.camera].genai.objects.length === 0 ||
+          config.cameras[search.camera].genai.objects.includes(
+            search.label,
+          )) ? (
+          <>
+            <div className="text-sm text-primary/40">Description</div>
+            <div className="flex h-64 flex-col items-center justify-center gap-3 border p-4 text-sm text-primary/40">
+              <div className="flex">
+                <ActivityIndicator />
+              </div>
+              <div className="flex">
+                Frigate will not request a description from your Generative AI
+                provider until the tracked object's lifecycle has ended.
+              </div>
+            </div>
+          </>
+        ) : (
+          <>
+            <div className="text-sm text-primary/40">Description</div>
+            <Textarea
+              className="h-64"
+              placeholder="Description of the tracked object"
+              value={desc}
+              onChange={(e) => setDesc(e.target.value)}
+            />
+          </>
+        )}
+
         <div className="flex w-full flex-row justify-end gap-2">
-          {config?.cameras[search.camera].genai.enabled && (
-            <div className="flex items-center">
+          {config?.cameras[search.camera].genai.enabled && search.end_time && (
+            <div className="flex items-start">
               <Button
                 className="rounded-r-none border-r-0"
                 aria-label="Regenerate tracked object description"
@@ -516,13 +543,16 @@ function ObjectDetailsTab({
               )}
             </div>
           )}
-          <Button
-            variant="select"
-            aria-label="Save"
-            onClick={updateDescription}
-          >
-            Save
-          </Button>
+          {(config?.cameras[search.camera].genai.enabled && search.end_time) ||
+            (!config?.cameras[search.camera].genai.enabled && (
+              <Button
+                variant="select"
+                aria-label="Save"
+                onClick={updateDescription}
+              >
+                Save
+              </Button>
+            ))}
         </div>
       </div>
     </div>

web/src/components/settings/SearchSettings.tsx

@@ -46,7 +46,7 @@ export default function SearchSettings({
   const trigger = (
     <Button
       className="flex items-center gap-2"
-      aria-label="Search Settings"
+      aria-label="Explore Settings"
       size="sm"
     >
       <FaCog className="text-secondary-foreground" />

web/src/pages/Explore.tsx

@@ -328,12 +328,12 @@ export default function Explore() {
           <div className="flex max-w-96 flex-col items-center justify-center space-y-3 rounded-lg bg-background/50 p-5">
             <div className="my-5 flex flex-col items-center gap-2 text-xl">
               <TbExclamationCircle className="mb-3 size-10" />
-              <div>Search Unavailable</div>
+              <div>Explore is Unavailable</div>
             </div>
             {embeddingsReindexing && allModelsLoaded && (
               <>
                 <div className="text-center text-primary-variant">
-                  Search can be used after tracked object embeddings have
+                  Explore can be used after tracked object embeddings have
                   finished reindexing.
                 </div>
                 <div className="pt-5 text-center">
@@ -384,8 +384,8 @@ export default function Explore() {
               <>
                 <div className="text-center text-primary-variant">
                   Frigate is downloading the necessary embeddings models to
-                  support semantic searching. This may take several minutes
-                  depending on the speed of your network connection.
+                  support the Semantic Search feature. This may take several
+                  minutes depending on the speed of your network connection.
                 </div>
                 <div className="flex w-96 flex-col gap-2 py-5">
                   <div className="flex flex-row items-center justify-center gap-2">

web/src/pages/Settings.tsx

@@ -40,7 +40,7 @@ import UiSettingsView from "@/views/settings/UiSettingsView";
 
 const allSettingsViews = [
   "UI settings",
-  "search settings",
+  "explore settings",
   "camera settings",
   "masks / zones",
   "motion tuner",
@@ -175,7 +175,7 @@ export default function Settings() {
       </div>
       <div className="mt-2 flex h-full w-full flex-col items-start md:h-dvh md:pb-24">
         {page == "UI settings" && <UiSettingsView />}
-        {page == "search settings" && (
+        {page == "explore settings" && (
           <SearchSettingsView setUnsavedChanges={setUnsavedChanges} />
         )}
         {page == "debug" && (

web/src/types/frigateConfig.ts

@@ -142,6 +142,7 @@ export interface CameraConfig {
     password: string | null;
     port: number;
     user: string | null;
+    tls_insecure: boolean;
   };
   record: {
     enabled: boolean;

web/src/views/live/LiveCameraView.tsx

@@ -17,7 +17,12 @@ import {
   DropdownMenuItem,
   DropdownMenuTrigger,
 } from "@/components/ui/dropdown-menu";
-import { TooltipProvider } from "@/components/ui/tooltip";
+import {
+  Tooltip,
+  TooltipContent,
+  TooltipProvider,
+  TooltipTrigger,
+} from "@/components/ui/tooltip";
 import { useResizeObserver } from "@/hooks/resize-observer";
 import useKeyboardListener from "@/hooks/use-keyboard-listener";
 import { CameraConfig, FrigateConfig } from "@/types/frigateConfig";
@@ -29,6 +34,7 @@ import {
 import { CameraPtzInfo } from "@/types/ptz";
 import { RecordingStartingPoint } from "@/types/record";
 import React, {
+  ReactNode,
   useCallback,
   useEffect,
   useMemo,
@@ -518,6 +524,53 @@ export default function LiveCameraView({
   );
 }
 
+type TooltipButtonProps = {
+  label: string;
+  onClick?: () => void;
+  onMouseDown?: (e: React.MouseEvent) => void;
+  onMouseUp?: (e: React.MouseEvent) => void;
+  onTouchStart?: (e: React.TouchEvent) => void;
+  onTouchEnd?: (e: React.TouchEvent) => void;
+  children: ReactNode;
+  className?: string;
+};
+
+function TooltipButton({
+  label,
+  onClick,
+  onMouseDown,
+  onMouseUp,
+  onTouchStart,
+  onTouchEnd,
+  children,
+  className,
+  ...props
+}: TooltipButtonProps) {
+  return (
+    <TooltipProvider>
+      <Tooltip>
+        <TooltipTrigger asChild>
+          <Button
+            aria-label={label}
+            onClick={onClick}
+            onMouseDown={onMouseDown}
+            onMouseUp={onMouseUp}
+            onTouchStart={onTouchStart}
+            onTouchEnd={onTouchEnd}
+            className={className}
+            {...props}
+          >
+            {children}
+          </Button>
+        </TooltipTrigger>
+        <TooltipContent>
+          <p>{label}</p>
+        </TooltipContent>
+      </Tooltip>
+    </TooltipProvider>
+  );
+}
+
 function PtzControlPanel({
   camera,
   clickOverlay,
@@ -611,8 +664,8 @@ function PtzControlPanel({
     >
       {ptz?.features?.includes("pt") && (
         <>
-          <Button
-            aria-label="Move PTZ camera to the left"
+          <TooltipButton
+            label="Move camera left"
             onMouseDown={(e) => {
               e.preventDefault();
               sendPtz("MOVE_LEFT");
@@ -625,9 +678,9 @@ function PtzControlPanel({
             onTouchEnd={onStop}
           >
             <FaAngleLeft />
-          </Button>
-          <Button
-            aria-label="Move PTZ camera up"
+          </TooltipButton>
+          <TooltipButton
+            label="Move camera up"
             onMouseDown={(e) => {
               e.preventDefault();
               sendPtz("MOVE_UP");
@@ -640,9 +693,9 @@ function PtzControlPanel({
             onTouchEnd={onStop}
           >
             <FaAngleUp />
-          </Button>
-          <Button
-            aria-label="Move PTZ camera down"
+          </TooltipButton>
+          <TooltipButton
+            label="Move camera down"
             onMouseDown={(e) => {
               e.preventDefault();
               sendPtz("MOVE_DOWN");
@@ -655,9 +708,9 @@ function PtzControlPanel({
             onTouchEnd={onStop}
           >
             <FaAngleDown />
-          </Button>
-          <Button
-            aria-label="Move PTZ camera to the right"
+          </TooltipButton>
+          <TooltipButton
+            label="Move camera right"
             onMouseDown={(e) => {
               e.preventDefault();
               sendPtz("MOVE_RIGHT");
@@ -670,13 +723,13 @@ function PtzControlPanel({
             onTouchEnd={onStop}
           >
             <FaAngleRight />
-          </Button>
+          </TooltipButton>
         </>
       )}
       {ptz?.features?.includes("zoom") && (
         <>
-          <Button
-            aria-label="Zoom PTZ camera in"
+          <TooltipButton
+            label="Zoom in"
             onMouseDown={(e) => {
               e.preventDefault();
               sendPtz("ZOOM_IN");
@@ -689,9 +742,9 @@ function PtzControlPanel({
             onTouchEnd={onStop}
           >
             <MdZoomIn />
-          </Button>
-          <Button
-            aria-label="Zoom PTZ camera out"
+          </TooltipButton>
+          <TooltipButton
+            label="Zoom out"
             onMouseDown={(e) => {
               e.preventDefault();
               sendPtz("ZOOM_OUT");
@@ -704,45 +757,60 @@ function PtzControlPanel({
             onTouchEnd={onStop}
           >
             <MdZoomOut />
-          </Button>
+          </TooltipButton>
         </>
       )}
+
       {ptz?.features?.includes("pt-r-fov") && (
-        <>
-          <Button
-            className={`${clickOverlay ? "text-selected" : "text-primary"}`}
-            aria-label="Click in the frame to center the PTZ camera"
-            onClick={() => setClickOverlay(!clickOverlay)}
-          >
-            <TbViewfinder />
-          </Button>
-        </>
+        <TooltipProvider>
+          <Tooltip>
+            <TooltipTrigger asChild>
+              <Button
+                className={`${clickOverlay ? "text-selected" : "text-primary"}`}
+                aria-label="Click in the frame to center the camera"
+                onClick={() => setClickOverlay(!clickOverlay)}
+              >
+                <TbViewfinder />
+              </Button>
+            </TooltipTrigger>
+            <TooltipContent>
+              <p>{clickOverlay ? "Disable" : "Enable"} click to move</p>
+            </TooltipContent>
+          </Tooltip>
+        </TooltipProvider>
       )}
       {(ptz?.presets?.length ?? 0) > 0 && (
-        <DropdownMenu modal={!isDesktop}>
-          <DropdownMenuTrigger asChild>
-            <Button aria-label="PTZ camera presets">
-              <BsThreeDotsVertical />
-            </Button>
-          </DropdownMenuTrigger>
-          <DropdownMenuContent
-            className="scrollbar-container max-h-[40dvh] overflow-y-auto"
-            onCloseAutoFocus={(e) => e.preventDefault()}
-          >
-            {ptz?.presets.map((preset) => {
-              return (
-                <DropdownMenuItem
-                  key={preset}
-                  aria-label={preset}
-                  className="cursor-pointer"
-                  onSelect={() => sendPtz(`preset_${preset}`)}
+        <TooltipProvider>
+          <Tooltip>
+            <TooltipTrigger asChild>
+              <DropdownMenu modal={!isDesktop}>
+                <DropdownMenuTrigger asChild>
+                  <Button aria-label="PTZ camera presets">
+                    <BsThreeDotsVertical />
+                  </Button>
+                </DropdownMenuTrigger>
+                <DropdownMenuContent
+                  className="scrollbar-container max-h-[40dvh] overflow-y-auto"
+                  onCloseAutoFocus={(e) => e.preventDefault()}
                 >
-                  {preset}
-                </DropdownMenuItem>
-              );
-            })}
-          </DropdownMenuContent>
-        </DropdownMenu>
+                  {ptz?.presets.map((preset) => (
+                    <DropdownMenuItem
+                      key={preset}
+                      aria-label={preset}
+                      className="cursor-pointer"
+                      onSelect={() => sendPtz(`preset_${preset}`)}
+                    >
+                      {preset}
+                    </DropdownMenuItem>
+                  ))}
+                </DropdownMenuContent>
+              </DropdownMenu>
+            </TooltipTrigger>
+            <TooltipContent>
+              <p>PTZ camera presets</p>
+            </TooltipContent>
+          </Tooltip>
+        </TooltipProvider>
       )}
     </div>
   );

web/src/views/settings/SearchSettingsView.tsx

@@ -91,7 +91,7 @@ export default function SearchSettingsView({
       )
       .then((res) => {
         if (res.status === 200) {
-          toast.success("Search settings have been saved.", {
+          toast.success("Explore settings have been saved.", {
             position: "top-center",
           });
           setChangedValue(false);
@@ -128,7 +128,7 @@ export default function SearchSettingsView({
     if (changedValue) {
       addMessage(
         "search_settings",
-        `Unsaved search settings changes`,
+        `Unsaved Explore settings changes`,
         undefined,
         "search_settings",
       );
@@ -140,7 +140,7 @@ export default function SearchSettingsView({
   }, [changedValue]);
 
   useEffect(() => {
-    document.title = "Search Settings - Frigate";
+    document.title = "Explore Settings - Frigate";
   }, []);
 
   if (!config) {
@@ -152,7 +152,7 @@ export default function SearchSettingsView({
       <Toaster position="top-center" closeButton={true} />
       <div className="scrollbar-container order-last mb-10 mt-2 flex h-full w-full flex-col overflow-y-auto rounded-lg border-[1px] border-secondary-foreground bg-background_alt p-2 md:order-none md:mb-0 md:mr-2 md:mt-0">
         <Heading as="h3" className="my-2">
-          Search Settings
+          Explore Settings
         </Heading>
         <Separator className="my-2 flex bg-secondary" />
         <Heading as="h4" className="my-2">
@@ -221,7 +221,7 @@ export default function SearchSettingsView({
               <div className="text-md">Model Size</div>
               <div className="space-y-1 text-sm text-muted-foreground">
                 <p>
-                  The size of the model used for semantic search embeddings.
+                  The size of the model used for Semantic Search embeddings.
                 </p>
                 <ul className="list-disc pl-5 text-sm">
                   <li>